Consider a set/mixture of continuous, correlated, and censored components/chemicals that are reasonable to combine in an index and share a common outcome. These components are also interval-censored between zero and upper thresholds, or detection limits, that may be different among the components. The `miWQS` package applies the multiple imputation (MI) procedure to the weighted quantile sum regression (WQS) methodology for continuous, binary, or count outcomes. In summary, MI consists of three stages: (1) imputation, (2) analysis, and (3) pooling. First, the missing values are imputed by bootstrapping (Lubin et.al (2004)